scholarly journals CHANGE DETECTION IN PHOTOGRAMMETRIC POINT CLOUDS FOR MONITORING OF ALPINE, GRAVITATIONAL MASS MOVEMENTS

2020 ◽  
Vol V-2-2020 ◽  
pp. 687-693
Author(s):  
A. Dinkel ◽  
L. Hoegner ◽  
A. Emmert ◽  
L. Raffl ◽  
U. Stilla
Keyword(s):  
Change Detection ◽  
Noise Level ◽  
Point Clouds ◽  
Bundle Adjustment ◽  
Gravitational Mass ◽  
Ground Control ◽  
Mass Movements ◽  
Control Points ◽  
The Third ◽  
Ground Control Points

Abstract. This contribution discusses the accuracy and the applicability of Photogrammetric point clouds based on dense image matching for the monitoring of gravitational mass movements caused by crevices. Four terrestrial image sequences for three different time epochs have been recorded and oriented using ground control point in a local reference frame. For the first epoch, two sequences are recorded, one in the morning and one in the afternoon to evaluate the noise level within the point clouds for a static geometry and changing light conditions. The second epoch is recorded a few months after the first epoch where also no significant change has occurred in between. The third epoch is recorded after one year with changes detected. As all point clouds are given in the same local coordinate frame and thus are co-registered via the ground control points, change detection is based on calculating the Multiscale-Model-to-Model-Cloud distances (M3C2) of the point clouds. Results show no movements for the first year, but identify significant movements comparing the third epoch taken in the second year. Besides the noise level estimation, the quality checks include the accuracy of the camera orientations based on ground control points, the covariances of the bundle adjustment, and a comparison the Geodetic measurements of additional control points and a laser scanning point cloud of a part of the crevice. Additionally, geological measurements of the movements have been performed using extensometers.

scholarly journals Short Communication: A simple workflow for robust low-cost UAV-derived change detection without ground control points

2019 ◽  
Author(s):  
Kristen L. Cook ◽  
Michael Dietze
Keyword(s):  
Change Detection ◽  
Low Cost ◽  
Point Clouds ◽  
Standard Approach ◽  
Ground Control ◽  
Control Points ◽  
Ground Control Points ◽  
3D Point Clouds ◽  
Tectonically Active ◽  
Comparative Accuracy

Abstract. High quality 3D point clouds generated from repeat camera-equipped unmanned aerial vehicle (UAV) surveys are increasingly being used to investigate landscape changes and geomorphic processes. Point cloud quality can be expressed as accuracy in a comparative (i.e., from survey to survey) and absolute (between survey and an external reference system) sense. Here we present a simple workflow for calculating pairs or sets of point clouds with a high comparative accuracy, without the need for ground control points or a dGPS equipped UAV. We demonstrate the efficacy of the new approach using a consumer-grade UAV in two contrasting landscapes: the coastal cliffs on the Island of Rügen, Germany, and the tectonically active Daan River gorge in Taiwan. Compared to a standard approach using ground control points, our workflow results in a nearly identical distribution of measured changes. Compared to a standard approach without ground control, our workflow reduces the level of change detection from several meters to 10–15 cm. This approach enables robust change detection using UAVs in settings where ground control is not possible.

scholarly journals Short Communication: A simple workflow for robust low-cost UAV-derived change detection without ground control points

2019 ◽  
Vol 7 (4) ◽  
pp. 1009-1017 ◽  
Author(s):  
Kristen L. Cook ◽  
Michael Dietze
Keyword(s):  
Change Detection ◽  
Low Cost ◽  
Point Clouds ◽  
Standard Approach ◽  
Ground Control ◽  
Control Points ◽  
Ground Control Points ◽  
Tectonically Active ◽  
Comparative Accuracy ◽  
Coastal Cliffs

Abstract. High-quality 3-D point clouds generated from repeat camera-equipped unmanned aerial vehicle (UAV) surveys are increasingly being used to investigate landscape changes and geomorphic processes. Point cloud quality can be expressed as accuracy in a comparative (i.e., from survey to survey) and absolute (between survey and an external reference system) sense. Here we present a simple workflow for calculating pairs or sets of point clouds with a high comparative accuracy, without the need for ground control points or a differential GNSS (dGNSS)-equipped UAV. The method is based on the automated detection of common tie points in stable portions of the survey area. We demonstrate the efficacy of the new approach using a consumer-grade UAV in two contrasting landscapes: the coastal cliffs on the island of Rügen, Germany, and the tectonically active Daan River gorge in Taiwan. Compared to a standard approach using ground control points, our workflow results in a nearly identical distribution of measured changes. Compared to a standard approach without ground control, our workflow reduces the level of change detection from several meters to 10–15 cm. This approach enables robust change detection using UAVs in settings where ground control is not feasible.

scholarly journals PRECISION OF VISUAL LOCALIZATION USING DYNAMIC GROUND CONTROL POINTS

2020 ◽  
Vol XLIII-B1-2020 ◽  
pp. 363-370
Author(s):  
P. Trusheim ◽  
C. Heipke
Keyword(s):  
Rapid Development ◽  
Sliding Window ◽  
Bundle Adjustment ◽  
Ground Control ◽  
Visual Localization ◽  
Control Points ◽  
Automated Driving ◽  
Sliding Windows ◽  
Ground Control Points

Abstract. Localization is one of the first steps in navigation. Especially due to the rapid development in automated driving, a precise and reliable localization becomes essential. In this paper, we report an investigation of the usage of dynamic ground control points (GCP) in visual localization in an automotive environment. Instead of having fixed positions, dynamic GCPs move together with the camera. As a measure of quality, we employ the precision of the bundle adjustment results. In our experiments, we simulate and investigate different realistic traffic scenarios. After investigating the role of tie points, we compare an approach using dynamic GCPs to an approach with static GCPs to answer the question how a comparable precision can be reached for visual localization. We show, that in our scenario, where two dynamic GCPs move together with a camera, similar results are indeed obtained to using a number of static GCPs distributed over the whole trajectory. In another experiment, we take a closer look at sliding window bundle adjustments. Sliding windows make it possible to work with an arbitrarily large number of images and to still obtain near real-time results. We investigate this approach in combination with dynamic GCPs and vary the no. of images per window.

scholarly journals AUTOMATIC KAPPA ANGLE ESTIMATION FOR AIR PHOTOS BASED ON PHASE ONLY CORRELATION

2016 ◽  
Vol XLI-B3 ◽  
pp. 131-135
Author(s):  
Z. Xiong ◽  
D. Stanley ◽  
Y. Xin
Keyword(s):  
Bundle Adjustment ◽  
Ground Control ◽  
Correlation Technique ◽  
Control Points ◽  
Initial Value ◽  
Ground Control Points ◽  
Attitude Angle ◽  
Camera Position ◽  
Air Photo ◽  
Orientation Parameters

The approximate value of exterior orientation parameters is needed for air photo bundle adjustment. Usually the air borne GPS/IMU can provide the initial value for the camera position and attitude angle. However, in some cases, the camera’s attitude angle is not available due to lack of IMU or other reasons. In this case, the kappa angle needs to be estimated for each photo before bundle adjustment. The kappa angle can be obtained from the Ground Control Points (GCPs) in the photo. Unfortunately it is not the case that enough GCPs are always available. In order to overcome this problem, an algorithm is developed to automatically estimate the kappa angle for air photos based on phase only correlation technique. This function has been embedded in PCI software. Extensive experiments show that this algorithm is fast, reliable, and stable.

scholarly journals Determining the Optimal Number of Ground Control Points for Varying Study Sites through Accuracy Evaluation of Unmanned Aerial System-Based 3D Point Clouds and Digital Surface Models

Drones ◽  
2020 ◽  
Vol 4 (3) ◽  
pp. 49 ◽  
Author(s):  
Jae Jin Yu ◽  
Dong Woo Kim ◽  
Eun Jung Lee ◽  
Seung Woo Son
Keyword(s):  
Image Processing ◽  
Point Clouds ◽  
Optimal Number ◽  
Ground Control ◽  
Control Points ◽  
Widespread Application ◽  
Ground Control Points ◽  
3D Point Clouds ◽  
Surface Models ◽  
Study Sites

The rapid development of drone technologies, such as unmanned aerial systems (UASs) and unmanned aerial vehicles (UAVs), has led to the widespread application of three-dimensional (3D) point clouds and digital surface models (DSMs). Due to the number of UAS technology applications across many fields, studies on the verification of the accuracy of image processing results have increased. In previous studies, the optimal number of ground control points (GCPs) was determined for a specific area of a study site by increasing or decreasing the amount of GCPs. However, these studies were mainly conducted in a single study site, and the results were not compared with those from various study sites. In this study, to determine the optimal number of GCPs for modeling multiple areas, the accuracy of 3D point clouds and DSMs were analyzed in three study sites with different areas according to the number of GCPs. The results showed that the optimal number of GCPs was 12 for small and medium sites (7 and 39 ha) and 18 for the large sites (342 ha) based on the overall accuracy. If these results are used for UAV image processing in the future, accurate modeling will be possible with minimal effort in GCPs.

scholarly journals Reconstructing 3D coastal cliffs from airborne oblique photographs without ground control points

2014 ◽  
Vol II-5 ◽  
pp. 113-116 ◽  
Author(s):  
T. J. B. Dewez
Keyword(s):  
Laser Scanner ◽  
Point Clouds ◽  
Ground Control ◽  
Control Points ◽  
Open Door ◽  
View Point ◽  
Ground Control Points ◽  
3D Point Clouds ◽  
Coastal Cliff ◽  
Coastal Cliffs

Coastal cliff collapse hazard assessment requires measuring cliff face topography at regular intervals. Terrestrial laser scanner techniques have proven useful so far but are expensive to use either through purchasing the equipment or through survey subcontracting. In addition, terrestrial laser surveys take time which is sometimes incompatible with the time during with the beach is accessible at low-tide. By comparison, structure from motion techniques (SFM) are much less costly to implement, and if airborne, acquisition of several kilometers of coastline can be done in a matter of minutes. In this paper, the potential of GPS-tagged oblique airborne photographs and SFM techniques is examined to reconstruct chalk cliff dense 3D point clouds without Ground Control Points (GCP). The focus is put on comparing the relative 3D point of views reconstructed by Visual SFM with their synchronous Solmeta Geotagger Pro2 GPS locations using robust estimators. With a set of 568 oblique photos, shot from the open door of an airplane with a triplet of synchronized Nikon D7000, GPS and SFM-determined view point coordinates converge to X: ±31.5 m; Y: ±39.7 m; Z: ±13.0 m (LE66). Uncertainty in GPS position affects the model scale, angular attitude of the reference frame (the shoreline ends up tilted by 2°) and absolute positioning. Ground Control Points cannot be avoided to orient such models.

scholarly journals 3-D modelling and visualization of large building using photogrammetric approach

2021 ◽  
Author(s):  
Raad Awad Kattan ◽  
◽  
Farsat Heeto Abdulrahman ◽  
Sami Mamlook Gilyana ◽  
Yousif Youkhna Zaya ◽  
...  
Keyword(s):  
Bundle Adjustment ◽  
Ground Control ◽  
Control Points ◽  
Distance Measurements ◽  
Ground Control Points ◽  
Digital Elevation ◽  
Elevation Model ◽  
College Of Engineering ◽  
User Friendly ◽  
D Model

The progress in modern technologies such as precise lightweight cameras mounted on unmanned aerial vehicles (UAV) and the more user-friendly software in the photogrammetric field, allows for 3-D model construction of any structure or shape. Software now achieves in sequence the processes of matching, generating tie points, block bundle adjustment, and generating digital elevation models.The aim of this study is to make a virtual 3-D model of the college of engineering /University of Duhok. Kurdistan Region, Iraq. The data input is vertical and oblique imagery acquired by UAV, ground control points distributed on the surrounded ground, facades, and roof. Ground control points were measured by the GPS RTK system in addition to the reflectorless total station instrument. The data is processed mainly using Agisoft PhotoScan software as well as the Global Mapper and the ReCap software. The output is a 3-D model, digital elevation model, and orthomosaic.Geometric and visual inspections were carried out. Some imperfections appeared on the sharp edges and parapets of the building. In the geometric accuracy of selected points on the building, the maximum standard deviation in the coordinates was ±4cm. The relative accuracy in distance measurements were in the range of 0.72% to 4.92 %

UAV-derived change detection without ground control points, an example from the cliff coast of Rügen

2020 ◽  
Author(s):  
Kristen Cook ◽  
Michael Dietze
Keyword(s):  
Change Detection ◽  
Subsurface Water ◽  
Ground Control ◽  
Control Points ◽  
Model Quality ◽  
Antecedent Precipitation ◽  
Ground Control Points ◽  
Comparative Accuracy ◽  
Coastal Cliffs ◽  
Aerial Vehicle

<p><span>High resolution topographic models generated from repeat unmanned aerial vehicle (UAV) surveys and structure from motion (SfM) are increasingly being used to investigate landscape changes and geomorphic processes. Traditionally, accurate UAV surveys require the use of independently measured ground control points or highly accurate camera position measurements. However, in addition to accuracy in an absolute sense (how well modeled topography matches real topography), model quality can be expressed as accuracy in a comparative sense (the degree to which two models match each other). We present a simple SfM workflow for calculating pairs or sets of models with a high comparative accuracy, without the need for ground control points or a d</span><span>G</span><span>NSS equipped </span><span>UAV. The method is based on the automated detection of common tie points in stable portions of the survey area and, c</span><span>ompared to a standard SfM approach without ground control, reduces the level of change detection in our surveys from several meters to 10-15 cm. </span><span>We apply this</span><span> approach in a multi-year monitoring campaign of an 8 km stretch of coastal cliffs on the island of Rügen, Germany. We are able to detect numerous mass wasting events as well as bands of more diffuse erosion in chalk sections of the cliff. Both the cliff collapses and the diffuse erosion appear to be strongly influenced by antecedent precipitation over seasonal timescales, with much greater activity during the winter of 2017-2018, following an above average wet summer, than during the subsequent two winters, which both followed relatively dry summers. This points to the influence of subsurface water storage in modulating cliff erosion on Rügen.</span></p>

scholarly journals Impact of UAV Surveying Parameters on Mixed Urban Landuse Surface Modelling

2020 ◽  
Vol 9 (11) ◽  
pp. 656
Author(s):  
Muhammad Hamid Chaudhry ◽  
Anuar Ahmad ◽  
Qudsia Gulzar
Keyword(s):  
Point Cloud ◽  
Large Scale ◽  
Accuracy Assessment ◽  
Computational Cost ◽  
Three Dimensional ◽  
Point Clouds ◽  
Ground Control ◽  
Control Points ◽  
Ground Control Points ◽  
High Computational Cost

Unmanned Aerial Vehicles (UAVs) as a surveying tool are mainly characterized by a large amount of data and high computational cost. This research investigates the use of a small amount of data with less computational cost for more accurate three-dimensional (3D) photogrammetric products by manipulating UAV surveying parameters such as flight lines pattern and image overlap percentages. Sixteen photogrammetric projects with perpendicular flight plans and a variation of 55% to 85% side and forward overlap were processed in Pix4DMapper. For UAV data georeferencing and accuracy assessment, 10 Ground Control Points (GCPs) and 18 Check Points (CPs) were used. Comparative analysis was done by incorporating the median of tie points, the number of 3D point cloud, horizontal/vertical Root Mean Square Error (RMSE), and large-scale topographic variations. The results show that an increased forward overlap also increases the median of the tie points, and an increase in both side and forward overlap results in the increased number of point clouds. The horizontal accuracy of 16 projects varies from ±0.13m to ±0.17m whereas the vertical accuracy varies from ± 0.09 m to ± 0.32 m. However, the lowest vertical RMSE value was not for highest overlap percentage. The tradeoff among UAV surveying parameters can result in high accuracy products with less computational cost.

scholarly journals Accuracy of Unmanned Aerial Vehicle (UAV) and SfM Photogrammetry Survey as a Function of the Number and Location of Ground Control Points Used

2018 ◽  
Vol 10 (10) ◽  
pp. 1606 ◽  
Author(s):  
Enoc Sanz-Ablanedo ◽  
Jim Chandler ◽  
José Rodríguez-Pérez ◽  
Celestino Ordóñez
Keyword(s):  
Critical Role ◽  
Bundle Adjustment ◽  
Ground Control ◽  
Control Points ◽  
Ground Sample ◽  
Ground Control Points ◽  
Check Points ◽  
Aerial Vehicle

The geometrical accuracy of georeferenced digital surface models (DTM) obtained from images captured by micro-UAVs and processed by using structure from motion (SfM) photogrammetry depends on several factors, including flight design, camera quality, camera calibration, SfM algorithms and georeferencing strategy. This paper focusses on the critical role of the number and location of ground control points (GCP) used during the georeferencing stage. A challenging case study involving an area of 1200+ ha, 100+ GCP and 2500+ photos was used. Three thousand, four hundred and sixty-five different combinations of control points were introduced in the bundle adjustment, whilst the accuracy of the model was evaluated using both control points and independent check points. The analysis demonstrates how much the accuracy improves as the number of GCP points increases, as well as the importance of an even distribution, how much the accuracy is overestimated when it is quantified only using control points rather than independent check points, and how the ground sample distance (GSD) of a project relates to the maximum accuracy that can be achieved.

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